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Using Par and Cex for Graphs

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Using Par and Cex for Graphs Using par and cex for graphs Michael Blasingame SCRG 2013 May 1 par • The func@on ‘par’ can be used to manipulate the current plot(s) • For example, it’s most commonly used to allow for mul@ple plots in one figure • Code example: par(mfrow = c(1, 3)) • Syntax interpretaon: Set my figure window to allow a 1 (row) by 3 (column) plong space par(mfrow=c(x,y)) par(new=T) • Some@mes, you want to be able to plot two different results on the same plot but can’t easily do this in one command due to dataset size • Example: Plot English and Spanish means of some effect with error bars, different colors, different lines, etc. • However, R will default to a new plot each me… par(new=T) • The command par(new=T) can be useful here • Syntax interpretaon: Keep the plot I just created ac@ve—don’t create a new one with this next command • Example (in this order): – plotmeans(data$Correct[data$TaskLang=="ENG”…) – par(new=T) – plotmeans(data$Correct[data$TaskLang=="SPN”…) par(new=T) par(new=T) • Quick caveat: par(new=T) only works if the axes are the same! You can’t plot a means plot and then an interac@on plot using par(new=T) par(mar=c(w,x,y,z) • Some@mes, your axes get crowded • Using the par(mar=c(w,x,y,z)) tells the plot how much space the bodom (w), lee (x), top (y), and right (z) sides get • Much of this depends on trial and error (just fiddling a bit un@l it looks like) par(mar=c(w,x,y,z)) • You can combine mar with other par features • Example: – par(mfrow=c(1,3),mar=c(5,5,5,2)) • Interpretaon: Give me a 1 (row) by 3 (column) plot with extra space on the bodom, lee, and top (but not a lot of space on the right) Area axis • Somemes, we want to override the axes labels, because R isn’t sure what our unique labeling system means Gross default axis • The axis parameter can be useful in overriding where labels are put • Example: – axis(1.5,1,"Clear Speech",cex.axis=1.5) – axis(1.5,2,"Plain Speech",cex.axis=1.5) • Interpretaon: First number indicates where in the ver@cal space; second number indicates which @ck mark. Third is “label”; fourth is size (more on cex in a minute) axis axis • Quick caveat: you must turn off your x-axis labels using xaxt='n’ • Example: – plot(data…., xaxt=‘n’, main=“Title”…) cex • The cex family tells you how big to magnify text • Default is ‘1’ • Family includes: – cex – cex.main – cex.axis – cex.lab cex – cex: for legends and other independent func@ons outside of the ‘plot’ family – cex.main: for @tles (must have a main=“…”) – cex.axis: for axes (within the ‘axis’ func@on) – cex.lab: for labels within the ‘plot’ family – Example: – plot(…. ,cex.lab=1.5,cex.main=2,….) – Interpretaon: magnify the labels by 1.5 and the @tle by 2 cex cex.main cex cex.label cex.axis legend • Legends orient the reader to your figure without you having to explain each symbol • Code: – legend("bodomlee",lty=c(2,1),col=c("black","dark red"),c("English","Spanish"),cex=1.5) – Interpretaon: legend(“placement”, symbol used, color of symbols, what the different symbols correspond to, magnificaon parameter) – NB: Placement can be “topright”, “toplee”, “boomright”, “boomlee” legend • ‘legend’ only works if there is a current plot open! • Not to be confused with par(new=T) • Also, no@ce how ‘cex’ is used (not ‘cex.label’, etc.) because ‘legend’ is its own separate command line (think of it as a mini-figure independent of the rest of the plot) plotmeans • Need library(gplots) • Calculates means of levels within a factor and plots mean + 95% confidence interval • User can specify CI confidence level (defaults to p = .95) and a variety of other parameters plotmeans • Example: – plotmeans(data$DependentVariable~data$Factor, lty=2, col=“darkred”, main=“Title”, xlab=“Factor”, ylab=“Response”,ylim=c(minDV,maxDV) ,ci.label=T, n.label=T, p = .95) – Interpretaon: plotmeans(dependent variable, factor (each level within the factor is separate), line type, color for line, @tle, factor group, response, y-axis range, #s for CI, n within each level, confidence level) – See slide 3 for example combining ‘plotmeans’ and ‘axis’ func@ons .
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